New Zealand head coach Scott Robertson says his time in Northern Ireland "helped shape" him as a person.

Tiernan Lynch says he has "mixed emotions" after a late goal condemned Larne to a 2-1 defeat at home to St Gallen in the Uefa Conference League.

Derry City manager Ruaidhri Higgins and midfielder Michael Duffy give their thoughts on the Candystripes' 2-0 defeat by Drogheda United in the FAI Cup final.

An old office block dubbed Belfast's 'ugliest building' is to be demolished.

Crowds gather at Douglas cenotaph in its 100th year to pay tribute to those killed in world wars.

Sandy Duthie's "dream job" involves solitude, a 160-year history, and a colony of little penguins.

The former first minister died suddenly last month after having a heart attack in North Macedonia.

Under co-option, parties can fill vacancies in the assembly and councils without holding a by-election.

The government has taken control of a decision over 8000 new homes near Sittingbourne.

Salford University's award-winning Centenary Building has been vacant for the past eight years.

Royal Guards fan 6 year old Frank Gates is preparing for Remembrance Day.

The memorial is moved to a prominent location after consultation with the Royal British Legion.

Twitter is one of the closest things we have today to a de facto "public space" on the internet.

Party platform calls corporate welfare ‘unsustainable,’ but its policies are a different story

I was recently asked to translate a large Excel file containing 40,000+ rows. The total word count was not so big, about 50k new words. With this article I would like to share my experience and problems processing this translation in … Continue reading →

1. Emploi : le taux de chômage remonte à 7,4 %  Actu Orange
2. Très légère hausse du chômage au troisième trimestre  Le Monde
3. À 7,4%, le taux de chômage repart à la hausse au troisième trimestre  BFM Business
4. Emploi : Le chômage remonte très légèrement mais fortement chez les jeunes  20 Minutes
5. Postes supprimés, plans sociaux... Le marché de l'emploi s'est déjà retourné  Europe 1

1. Democrat Ruben Gallego wins Arizona U.S. Senate race against Republican Kari Lake  The Globe and Mail
2. Ruben Gallego defeats Trump ally Kari Lake in Arizona Senate race  BBC.com
3. Democrat Gallego wins Arizona, Republicans hold 53-47 US Senate majority  Al Jazeera English

Regain d'intérêt pour l'actualité, méfiance toujours vive, place croissante des réseaux sociaux: ce sont quelques-uns des enseignements du baromètre annuel sur la confiance des Français dans les médias publié lundi par le journal La Croix.

. Actu: le rebond

Fait marquant de ce baromètre réalisé depuis 1987: le regain d'intérêt pour l'actualité. 76% des sondés (1.500 majeurs interrogés par internet ou téléphone selon la méthode des quotas) disent la suivre "avec un grand intérêt", contre 62% l'an passé.

"C'est le cinquième plus haut niveau en 35 ans", a souligné Jean-Christophe Ploquin, rédacteur en chef de La Croix, lors d'une conférence de presse. Cette proportion est cependant moindre chez les moins de 35 ans (66%).

En outre, quatre sondés sur dix disent s'intéresser davantage à l'actu qu'il y a quelques années. Cela coïncide avec "une actualité riche en 2022" (Ukraine, présidentielle en France...) après la période du Covid, a commenté Guillaume Caline, de l'institut Kantar Public, qui réalise ce baromètre.

C'est toutefois à nuancer par le fait qu'un sondé sur cinq (21%) s'y intéresse moins qu'avant, et même un sur trois (33%) chez les moins de 35 ans.

Et la moitié des sondés (51%) ressent "souvent de la lassitude" envers l'actualité, la fameuse "fatigue informationnelle" pointée par plusieurs études récemment.

. Trop ou pas assez ?

Le Mondial de football au Qatar (pour 48% des sondés), la mort de la reine d'Angleterre (43%) et la pénurie de carburant (40%): voilà les trois sujets dont les médias ont trop parlé en 2022.

A l'inverse, 51% jugent que les médias n'ont pas assez parlé du débat sur la fin de vie. Selon M. Caline, cela montre "l'intérêt des Français pour les sujets susceptibles de les toucher directement".

Le traitement de la guerre en Ukraine suscite des avis partagés: 41% pensent que les médias en ont parlé au juste niveau et 38% qu'ils en ont trop parlé.

. La télé centrale

Journaux télé, radio, chaînes info, sites internet, quotidiens papier, réseaux sociaux: chaque jour, les Français utilisent en moyenne près de 4 canaux pour s'informer.

Mais, dans cette "multiplicité des sources d'info", la télé "garde une place centrale", selon M. Caline. Ainsi, les JT sont le canal que les sondés privilégient pour s'informer au quotidien, quel que soit l'âge (35% sur l'ensemble du panel).

Chez les 18-24 ans, les réseaux sociaux arrivent deuxièmes, alors que cette place est occupée par les chaînes info dans toutes les autres classes d'âge.

. Méfiance, toujours

Même si le jugement est moins sévère que l'an dernier, la perte de confiance reste une tendance de fond. Plus de la moitié des sondés (54%) pense que, "la plupart du temps, il faut se méfier de ce que disent les médias sur les grands sujets d'actualité".

Pour autant, "ce réflexe de méfiance" existe surtout quand on considère les médias "de manière globale", en tant qu'"institution", a pondéré M. Caline: "Pris isolément, c'est bien moins négatif".

Ainsi, parmi les sondés qui s'informent via les JT, 73% leur font confiance. Cette proportion est aussi de 73% pour la radio, 66% pour les quotidiens nationaux mais seulement 46% pour les émissions d'actualité et de divertissement à la télé et 40% pour les influenceurs.

Par ailleurs, l'image des journalistes reste dégradée: 59% des sondés pensent qu'ils ne résistent pas aux pressions politiques et 56% à celles de l'argent.

. Jeunes et réseaux

Les réseaux sociaux "ont fait leur trou" comme source d'information, "notamment chez les plus jeunes", a noté M. Ploquin. Toutes générations confondues, 35% des sondés les utilisent quotidiennement dans ce but.

Paradoxalement, seuls 36% de ceux qui s'informent sur les réseaux leur font confiance.

Et le rapport à cette source d'information met en évidence "un fort clivage générationnel", selon M. Caline.

Ainsi, après 35 ans, 6 sondés sur 10 pensent que la diffusion sur les réseaux d'informations par "des personnes qui ne sont pas des médias ou des journalistes" est une mauvaise chose.

Une proportion qui s'inverse chez les plus jeunes: la moitié des moins de 35 ans juge au contraire que c'est une bonne chose.

In order to further improve the teaching quality of multimedia teaching in school daily teaching, a classroom facial expression emotion recognition model is proposed based on convolutional neural network. VGGNet and CliqueNet are used as the basic expression emotion recognition methods, and the two recognition models are fused while the attention module CBAM is added. Simulation results show that the designed classroom face expression emotion recognition model based on V-CNet has high recognition accuracy, and the recognition accuracy on the test set reaches 93.11%, which can be applied to actual teaching scenarios and improve the quality of classroom teaching.

To achieve psychological and emotional analysis of massive internet chats, researchers have used statistical methods, machine learning, and neural networks to analyse the dynamic tendencies of texts dynamically. For long readers, the author first compares and explores the differences between the two psychoanalysis algorithms based on the emotion dictionary and machine learning for simple sentences, then studies the expansion algorithm of the emotion dictionary, and finally proposes an extended text psychoanalysis algorithm based on conditional random field. According to the experimental results, the mental dictionary's accuracy, recall, and F-score based on the cognitive understanding of each additional ten words were calculated. The optimisation decreased, and the memory and F-score improved. An <i>F</i>-value greater than 1, which is the most effective indicator for evaluating the effectiveness of a mental analysis problem, can better demonstrate that the algorithm is adaptive in the literature dictionary. It has been proven that this scheme can achieve good results in analysing emotional tendencies and has higher efficiency than ordinary weight-based psychological sentiment analysis algorithms.

Based on a survey of 2548 American adults conducted by Pew Research Center in 2021, this study finds that trust in the accuracy of news circulated on X (former Twitter) is positively correlated with following news sites on X, underscoring the crucial role of trust in news accuracy in shaping news-seeking behaviour. Trust in news accuracy also positively relates to political participation via X. Those who trust in news accuracy are more likely to perceive X as an effective tool for raising public awareness about political and social issues, as well as a positive force for democracy. However, exposure to misinformation weakens the connection between trust in news accuracy and users' perception about X as an effective tool for raising public awareness about political or social issues and as a positive driver for democracy.

This paper examines the growing aspect of perceive organisational politics (POPs) in organisations by understanding their employee engagement with mediating effect of emotional intelligence. This study is cross-sectional, wherein a survey is conducted on executives of different sectors holding strategic positions. The purposive sampling technique is applied to find the 117 most suitable executives for this survey. The survey is self-administered, and a questionnaire is used as an instrument with 43 measurement scale items adopted from previous similar studies. Construct's reliability and validity followed by PLS-SEM is performed using JASP statistical application. The result revealed that the dimensionality support and validation of POP based on a new set of measures centred on generalised beliefs of the application and abuse of power, infrastructure, credibility, choice making, and line-of-sight. In line with previous findings, the current findings also showed that POP works as a barrier to individual behavioural demand and can negatively affect work efficiency. Existence of perceive organisational politics due to the normative belief of the situation happing in the organisation, disengagement of employees, and also evaluates new empirical insight into the organisation by mediating emotional intelligence.

Aim/Purpose: This study examines the use of the Emergency Remote Teaching (ERT) platform by undergraduates of the University of Ibadan, Nigeria, during the COVID-19 pandemic using the constructs of the UTAUT2 model. Five constructs of the UTAUT2 model were adopted to investigate the use of the ERT platform by undergraduates of the university. Background: The Coronavirus (COVID-19) outbreak disrupted academic activities in educational institutions, leading to an unprecedented school closure globally. In response to the pandemic, higher educational institutions adopted different initiatives aimed at ensuring the uninterrupted flow of their teaching and learning activities. However, there is little research on the use of ERT platforms by undergraduates in Nigerian universities. Methodology: The descriptive survey research design was adopted for the study. The multi-stage random sampling technique was used to select 334 undergraduates at the University of Ibadan, Nigeria, while a questionnaire was used to collect data from 271 students. Quantitative data were collected and analyzed using frequency counts, percentages, mean and standard deviation, Pearson Product Moment Correlation, and regression analysis. Contribution: The study contributes to understanding ERT use in the educational institutions of Nigeria – Africa’s most populous country. Furthermore, the study adds to the existing body of knowledge on how the UTAUT2 Model could explain the use of information technologies in different settings. Findings: Findings revealed that there was a positive significant relationship between habit, hedonic motivation, price value, and social influence on the use of ERT platforms by undergraduates. Hedonic motivation strongly predicted the use of ERT platforms by most undergraduates. Recommendations for Practitioners: As a provisional intervention in times of emergencies, the user interface, navigation, customization, and other aesthetic features of ERT platforms should be more appealing and enjoyable to ensure their optimum utilization by students. Recommendation for Researchers: More qualitative research is required on users’ satisfaction, concerns, and support systems for ERT platforms in educational institutions. Future studies could consider the use of ERT by students in different countries and contexts such as students participating in English as a Foreign Language (EFL) and the English for Speakers of other languages (ESOL) programs. Impact on Society: As society faces increased uncertainties of the next global pandemic, this article reiterates the crucial roles of information technology in enriching teaching and learning activities in educational institutions. Future Research: Future research should focus on how different technology theories and models could explain the use of ERT platforms at different educational institutions in other geographical settings and contexts.

Aim/Purpose: The study focused on learner sentiments and experiences after using the Moodle assessment module and trained a machine learning classifier for future sentiment predictions. Background: Learner assessment is one of the standard methods instructors use to measure students’ performance and ascertain successful teaching objectives. In pedagogical design, assessment planning is vital in lesson content planning to the extent that curriculum designers and instructors primarily think like assessors. Assessment aids students in redefining their understanding of a subject and serves as the basis for more profound research in that particular subject. Positive results from an evaluation also motivate learners and provide employment directions to the students. Assessment results guide not just the students but also the instructor. Methodology: A modified methodology was used for carrying out the study. The revised methodology is divided into two major parts: the text-processing phase and the classification model phase. The text-processing phase consists of stages including cleaning, tokenization, and stop words removal, while the classification model phase consists of dataset training using a sentiment analyser, a polarity classification model and a prediction validation model. The text-processing phase of the referenced methodology did not utilise tokenization and stop words. In addition, the classification model did not include a sentiment analyser. Contribution: The reviewed literature reveals two major omissions: sentiment responses on using the Moodle for online assessment, particularly in developing countries with unstable internet connectivity, have not been investigated, and variations of the k-fold cross-validation technique in detecting overfitting and developing a reliable classifier have been largely neglected. In this study we built a Sentiment Analyser for Learner Emotion Management using the Moodle for assessment with data collected from a Ghanaian tertiary institution and developed a classification model for future sentiment predictions by evaluating the 10-fold and the 5-fold techniques on prediction accuracy. Findings: After training and testing, the RF algorithm emerged as the best classifier using the 5-fold cross-validation technique with an accuracy of 64.9%. Recommendations for Practitioners: Instead of a closed-ended questionnaire for learner feedback assessment, the open-ended mechanism should be utilised since learners can freely express their emotions devoid of restrictions. Recommendation for Researchers: Feature selection for sentiment analysis does not always improve the overall accuracy for the classification model. The traditional machine learning algorithms should always be compared to either the ensemble or the deep learning algorithms Impact on Society: Understanding learners’ emotions without restriction is important in the educational process. The pedagogical implementation of lessons and assessment should focus on machine learning integration Future Research: To compare ensemble and deep learning algorithms

Dynamic nature of the FMCG sector perpetually provides a tricky challenge for organisational leaders to nurture their employees. High demand for products, less shelf life and tough competitors always challenge the leaders to uphold their products in the market. Due to technology and e-commerce, many new competitors have joined the market, vying with the industry's veterans. Due to their unique business models that match client needs, these firms are expected to boost FMCG industry income in the future. Managers' leadership styles depend primarily on emotional intelligence. This quantitative study examines how emotional intelligence influences West Bengal FMCG senior managers' leadership styles. 500 FMCG managers were selected. PLS-SEM is used to study. Emotionally competent leaders choose transactional and transformational leadership styles depending on the occasion. Managers' transactional leadership style is strongly influenced by their sympathetic awareness, as shown by a path coefficient of 0.755. Transformational leadership style has a path coefficient of 0.693, indicating that managers' empathy affects their organisational management. Thus, sympathetic awareness and emotion regulation predict good management leadership.

Aim/Purpose: Executive doctoral programs in higher education are under-researched. Scholars, administers, and students should be aware of all common delivery methods for higher education graduate programs. Background This paper provides a review and analysis of executive doctoral higher education programs in the United States. Methodology: Executive higher education doctoral programs analyzed utilizing a qualitative demographic market-based analysis approach. Contribution: This review of executive higher education doctoral programs provides one of the first investigations of this segment of the higher education degree market. Findings: There are twelve programs in the United States offering executive higher education degrees, though there are less aggressively marketed programs described as executive-style higher education doctoral programs that could serve students with similar needs. Recommendations for Practitioners: Successful executive higher education doctoral programs require faculty that have both theoretical knowledge and practical experience in higher education. As appropriate, these programs should include tenure-line, clinical-track, and adjunct faculty who have cabinet level experience in higher education. Recommendation for Researchers: Researchers should begin to investigate more closely the small but growing population of executive doctoral degree programs in higher education. Impact on Society: Institutions willing to offer executive degrees in higher education will provide training specifically for those faculty who are one step from an executive position within the higher education sector. Society will be impacted by having someone that is trained in the area who also has real world experience. Future Research: Case studies of students enrolled in executive higher education programs and research documenting university-employer goals for these programs would enhance our understanding of this branch of the higher education degree market.

Aim/Purpose: Although cassava is one of the crops that can be grown during the dry season in Northeastern Thailand, most farmers in the region do not know whether the crop can grow in their specific areas because the available agriculture planning guideline provides only a generic list of dry-season crops that can be grown in the whole region. The purpose of this research is to develop a predictive model that can be used to predict suitable areas for growing cassava in Northeastern Thailand during the dry season. Background: This paper develops a decision support system that can be used by farmers to assist them determine if cassava can be successfully grown in their specific areas. Methodology: This study uses satellite imagery and data on land characteristics to develop a machine learning model for predicting suitable areas for growing cassava in Thailand’s Nakhon-Phanom province. Contribution: This research contributes to the body of knowledge by developing a novel model for predicting suitable areas for growing cassava. Findings: This study identified elevation and Ferric Acrisols (Af) soil as the two most important features for predicting the best-suited areas for growing cassava in Nakhon-Phanom province, Thailand. The two-class boosted decision tree algorithm performs best when compared with other algorithms. The model achieved an accuracy of .886, and .746 F1-score. Recommendations for Practitioners: Farmers and agricultural extension agents will use the decision support system developed in this study to identify specific areas that are suitable for growing cassava in Nakhon-Phanom province, Thailand Recommendation for Researchers: To improve the predictive accuracy of the model developed in this study, more land and crop characteristics data should be incorporated during model development. The ground truth data for areas growing cassava should also be collected for a longer period to provide a more accurate sample of the areas that are suitable for cassava growing. Impact on Society: The use of machine learning for the development of new farming systems will enable farmers to produce more food throughout the year to feed the world’s growing population. Future Research: Further studies should be carried out to map other suitable areas for growing dry-season crops and to develop decision support systems for those crops.

Aim/Purpose: Any system that aims to address the task of modeling social media communication need to deal with the usage of emojis. Efficient prediction of the most likely emoji given the text of a message may help to improve different NLP tasks. Background: We explore two tasks: emoji identification and emoji prediction. While emoji prediction is a classification task of predicting the emojis that appear in a given text message, emoji identification is the complementary preceding task of determining if a given text message includes emojies. Methodology: We adopt a supervised Machine Learning (ML) approach. We compare two text representation approaches, i.e., n-grams and character n-grams and analyze the contribution of additional metadata features to the classification. Contribution: The task of emoji identification is novel. We extend the definition of the emoji prediction task by allowing to use not only the textual content but also meta-data analysis. Findings: Metadata improve the classification accuracy in the task of emoji identification. In the task of emoji prediction it is better to apply feature selection. Recommendations for Practitioners: In many of the cases the classifier decision seems fitter to the comment content than the emoji that was chosen by the commentator. The classifier may be useful for emoji suggestion. Recommendation for Researchers: Explore character-based representations rather than word-based representations in the case of morphologically rich languages. Impact on Society: Improve the modeling of social media communication. Future Research: We plan to address the multi-label setting of the emoji prediction task and to investigate the deep learning approach for both of our classification tasks

Aim/purpose The purpose of this article is to discuss the psychosocial and emotional outcomes of an introductory health science workshop designed to support and assist incoming health science students before starting their university study.   Background For the past two decades, a South Australian university offered an on-campus face to face workshop titled ‘Preparation for Health Sciences’ to incoming first-year students from eleven allied health programs such as Nursing, Physiotherapy and Medical Imaging. While many were locals, a good number came from regional and rural areas, and many were international students also. They consisted of both on-campus and off-campus students.   The workshop was created as a new learning environment that was available for students of diverse age groups, educational and cultural backgrounds to prepare them to study sciences. The content of the four-day workshop was developed in consultation with the program directors of the allied health programs. The objectives were to: introduce the assumed foundational science knowledge to undertake health sciences degree; gain confidence in approaching science subjects; experience lectures and laboratory activities; and become familiar with the University campus and its facilities. The workshop was delivered a week before the orientation week, before first-year formal teaching weeks. The topics covered were enhancing study skills, medical and anatomical terminology, body systems, basic chemistry and physics, laboratory activities, and assessment of learning.   Methodology In order to determine the outcomes of the workshop, a survey was used requiring participants to agree or disagree about statements concerning the preparatory course and answer open-ended questions relating to the most important information learned and the best aspects of the workshop. Several students piloted this questionnaire before use in order to ascertain the clarity of instructions, terminology and statements. The result of the 2015-2018 pre- and post-evaluation showed that the workshop raised confidence and enthusiasm in commencing university and that the majority considered the workshop useful overall. The findings of the survey are drawn upon to examine the psychosocial and emotional impacts of the workshop on participants. Using secondary qualitative analysis, the researchers identified the themes relating to the psychosocial and emotional issues conveyed by the participants.   Contribution The contributions of the article are in the areas of improving students’ confidence to complete their university degrees and increasing the likelihood of academic success. Findings Of the 285 students who participated in the workshops from 2015 to 2018, 166 completed the survey conducted at the conclusion of the initiative, representing a 58% response rate. The workshops achieved the objectives outlined at the outset. While there were many findings reported (Thalluri, 2016), the results highlighted in this paper relate to the psychosocial and emotional impacts of the workshop on students. Three themes emerged, and these were Increased preparedness and confidence; Networking and friendships that enhanced support, and Reduced anxiety to study sciences. Some drawbacks were also reported including the cost, time and travel involved. Recommendations for practitioners Students found the introductory workshop to be psychosocially and emotionally beneficial. It is recommended that the same approach be applied for teaching other challenging fields such as mathematics and physics within the university and in other contexts and institutions. Recommendations for researchers Improving and extending the workshop to provide greater accessibility and autonomy is recommended. A longitudinal study to follow up the durability of the workshop is also proposed. Impact on society The impacts in the broader community include: higher academic success for students; improved mental health due to social networking and friendship groups and reduced anxiety and fear; reduced dropout rate in their first year; greater potential to complete educational degrees; reduced wastage in human and financial resources; and increased human capital. Future research Addressing the limitations of cost, time and travel involved, and following-up with the participants’ academic and workplace performance are future directions for research.

Aim/Purpose. The study aimed to examine the remote and face-to-face experience of pedagogical training in kindergarten after the third COVID-19 closure in Israel. Background. The outbreak of the COVID-19 epidemic in 2020 changed the training system, and preservice teachers were required to have their practical experience in the kindergartens both remotely and face-to-face. They had to adapt to the new requirements of teacher training programs and receive professional coaching and support from the pedagogical instructor remotely. Methodology. The sample comprised 26 early childhood preservice teachers, who received academic training that includes proficiency in digital technology. The data were collected through feedback that they wrote themselves during the training period and analyzed in the interpretive approach. Contribution. The contribution of the present study is that it examines the pedagogical coaching from the perspective of preservice teachers in a kindergarten during the COVID-19 epidemic, which forced a transition from face-to-face to remote pedagogical training, then back to face-to-face pedagogical instruction. To the best of my knowledge, no such study has been carried out to date, which makes it unique. Findings. The main findings indicate the dissatisfaction of most preservice kindergarten teachers with the remote pedagogical training (about 85%) at the physical, emotional, technological, and pedagogical levels, and the satisfaction of most preservice kindergarten teachers with face-to-face pedagogical training (about 92%) at the physical, emotional, and pedagogical levels. The main conclusion is that technology is a potential barrier in training, and that preservice kindergarten teachers need a pedagogical instructor present at a professional face-to-face meeting. Recommendations for Practitioners. The findings of the study show how important in-person learning and engagement is for everyone especially for Preservice teachers’ and may be helpful for pedagogical coaching teams. Recommendations for Researchers. Preservice teachers’ awareness of the pedagogical coaching experiences could persuade the coaching teams to avoid potential difficulties, increase emotional support, and refine the use of technology to make it a closer substitute for frontal communication. Impact on Society. Face-to-face training based on interpersonal relationship, allows to develop better during the training period.

Aim/Purpose: This study explored teachers’ data-driven decision-making processes during routine and emergency remote teaching, as experienced during the COVID-19 pandemic. Background: Decision-making is essential in teaching, with informed decisions promoting student learning and teachers’ professional development most effectively. However, obstacles to the use of data have been identified in many studies. Methodology: Using a qualitative methodology (N=20), we studied how teachers make decisions, what data is available, and what data they would like to have to improve their decision-making. We used an inductive approach (bottom-up), utilizing teachers’ statements related to decision-making as the unit of analysis. Contribution: Our findings shed an important light on teachers’ Data-Driven Decision-Making (DDDM), highlighting the differences between routine and Emergency Remote Teaching (ERT). Findings: Overall, we found that teachers make teaching decisions in three main areas: pedagogy, discipline-related issues, and appearance and behavior. They shift between making decisions based on data and making decisions based on intuition. Academic-related decisions are the most prominent in routine teaching, and during ERT, they were almost the only area in which teachers’ decisions were made. Teachers reported collecting data about students’ academic achievements and emotional state and considered the organizational culture, consultation with colleagues, and parents’ involvement before decision-making. Recommendations for Practitioners: Promote a culture of data-driven decision-making across the education system; Make diverse and rich data of different types accessible to teachers; Increase professional and emotional support for teachers. Recommendation for Researchers: Researchers have the potential to expand the scope of this study by conducting research using other methodologies and in different countries. Impact on Society: This study highlights the importance of teachers’ data-driven decision-making in improving teaching practices and promoting students’ achievement. Future Research: Additional research is required to examine data-driven decision-making in diverse circumstances.

Breast cancer is leading cause of mortality among women compared to other types of cancers. Hence, early breast cancer diagnosis is crucial to the success of treatment. Various pathological and imaging tests are available for the diagnosis of breast cancer. However, it may introduce errors during detection and interpretation, leading to false-negative and false-positive results due to lack of pre-processing of it. To overcome this issue, we proposed a effective image pre-processing technique-based on Otsu's thresholding and single-seeded region growing (SSRG) to remove artefacts and segment the pectoral muscle from breast mammograms. To validate the proposed method, a publicly available MIAS dataset was utilised. The experimental finding showed that proposed technique improved 18% breast cancer detection accuracy compared to existing methods. The proposed methodology works efficiently for artefact removal and pectoral segmentation at different shapes and nonlinear patterns.

Aim/Purpose: The present study aims to frame the relationship between job and personal resources (namely, organizational identification and emotional intelligence), burnout, and musculoskeletal disorders (i.e., back pain, upper limb pain, lower limb discomfort), into the theoretical framework provided by the JD-R health model. Background: Empirical research indicates a connection between burnout and the onset of musculoskeletal problems, one of the most important occupational health issues affecting all jobs and organizations. In light of the JD-R health model, we investigated the association between personal and job resources with burnout and musculoskeletal disorders. Methodology: An anonymous online questionnaire was answered by 320 workers (82.4% female, Mage = 42.18; SDage = 12.24) investigating their perceived level of burnout, the presence of musculoskeletal pain (back, neck, and shoulder), and their level of organizational identification and emotional intelligence. Descriptive analysis, correlation, and moderated mediation model were performed using SPSS. Contribution: We confirmed the role of personal and organizational resources in the salutogenic process considered by the JD-R health model. Emotional intelligence, decreasing the perceived level of burnout, limited the development of musculoskeletal disorders. Moreover, when organizational identification presented low and medium levels, the association between emotional intelligence and burnout strengthened. Findings: Our results showed a negative, indirect effect of emotional intelligence on musculoskeletal disorders via burnout. Moreover, we found a moderation of organizational organization, indicating that at low and medium levels of identification, the association between emotional intelligence and burnout is stronger. Recommendation for Researchers: In addition to work factors involved in the link between burnout and musculoskeletal disorders, it is also important to consider personal and emotional factors, which can decrease the occurrence of adverse consequences. Future Research: Future research developments could contribute to a deeper understanding of the mechanisms linking emotional intelligence, burnout, and musculoskeletal problems, as well as consider objective indicators of burnout levels or consider using ecological data collection methodologies (e.g., ecological momentary assessment), to identify patterns and associations between burnout and musculoskeletal disorders.

[Meg O’Neill] 00:08 Hello and welcome to the Berkeley Technology Law Journal podcast. My name is Meg O’Neill and I am one of the editors of the podcast. Today we are excited to share with you a conversation between Berkeley Law LLM student Franco Dellafiori, and Professor Bertrall Ross. Professor ...

The post Berkeley Technology Law Journal Podcast: Will ChatGPT Tell Me How to Vote? Democracy & AI with Professor Bertrall Ross appeared first on Berkeley Technology Law Journal.

Congcong FANG,Yun JIN,Guanlin CHEN,Yunfan ZHANG,Shidang LI,Yong MA,Yue XIE, Vol.E107-D, No.11, pp.1463-1467
Currently, an increasing number of tasks in speech emotion recognition rely on the analysis of both speech and text features. However, there remains a paucity of research exploring the potential of leveraging large language models like GPT-3 to enhance emotion recognition. In this investigation, we harness the power of the GPT-3 model to extract semantic information from transcribed texts, generating text modal features with a dimensionality of 1536. Subsequently, we perform feature fusion, combining the 1536-dimensional text features with 1188-dimensional acoustic features to yield comprehensive multi-modal recognition outcomes. Our findings reveal that the proposed method achieves a weighted accuracy of 79.62% across the four emotion categories in IEMOCAP, underscoring the considerable enhancement in emotion recognition accuracy facilitated by integrating large language models.
Publication Date: 2024/11/01

Naoya NEZU,Hiroshi YAMADA, Vol.E107-D, No.11, pp.1408-1421
Modern memory devices such as DRAM are prone to errors that occur because of unintended bit flips during their operation. Since memory errors severely impact in-memory key-value stores (KVSes), software mechanisms for hardening them against memory errors are being explored. However, it is hard to efficiently test the memory error handling code due to its characteristics: the code is event-driven, the handlers depend on the memory object, and in-memory KVSes manage various objects in huge memory space. This paper presents MemFI that supports runtime tests for the memory error handlers of in-memory KVSes. Our approach performs the software fault injection of memory errors at the memory object level to trigger the target handler while smoothly carrying out tests on the same running state. To show the effectiveness of MemFI, we integrate error handling mechanisms into a real-world in-memory KVS, memcached 1.6.9 and Redis 6.2.7, and check their behavior using the MemFI prototypes. The results show that the MemFI-based runtime test allows us to check the behavior of the error handling mechanisms. We also show its efficiency by comparing it to other fault injection approaches based on a trial model.
Publication Date: 2024/11/01

We draw on the historiographical concepts of "generational units" and "collective memories" as a framework for understanding the emergence of entrepreneurially oriented cohesive groups within regions. Generational units are localized subgroups within generations that have a self-referential, reflexive quality, by virtue of the members' sense of their own connections to each other and the events that define them. Collective memories are shared accounts of the past shaped by historical events that mold individuals' perceptions. The two concepts provide a valuable point of departure for incorporating historical concepts into the study of entrepreneurial dynamics and offer a framework for understanding how entrepreneurs' historically situated experiences affect them. Our framework breaks new theoretical ground in several ways. First, we synthesize disparate literatures on generational units, collective memory, and organizational imprinting. Second, we specify mechanisms through which imprinting occurs and persists over time. We develop analytical arguments framed by sociological and historiographical theories, focusing on the conditions under which meaningful generational units of entrepreneurs may emerge and benefit from leadership and legacy building, technologies of memory, and institutional support that increases the likelihood of their persistence.

DURING my visit in 1985, I had met the management staff at the plantation in Ghana. The one I remember most was Al Doku.

He was the chief accountant, about 45 years old, working for the managing director, Bill Morrison.

At the meeting in Morrison’s office, he could remember the figures well, and I was impressed. It was just that he was quiet for most of the time, and I could see that his eyes were sad.

At that time, there were many reasons to feel that way. The cedi was devaluing every week, and to go for dinner in town was a major decision for it would involve bringing your money in big wads to pay for it.

This is despite the income from gold that Ghana was blessed with as well as cocoa, which has a flavour that commands a premium. The country also produces shea nut, the fruit of massive trees that grow in the north. The oil is like cocoa butter.

However, that year the food shortage was bad, even potatoes were hard to find. They had to be imported.

Morrison had helped with giving breakfast to the workers, and they would line up for the palm oil, tapioca and fish cooked in large pots in front of them before they started work for the day.

Due to the shortage of hard currency, the plantation too had to make do without many things, and building of workers’ houses was one of them as no imported material was used.

At the housing project for workers, I had no time to ask about Al Doku.

I watched Bill giving instructions to the building supervisor. He was using earth to make a thick wall to build a house, and when it was dry after a few days, he added another level, until the building had a coat of cement and more walls for the rooms. I had not seen a building made in that way before. Bill was thorough.

“Saves a lot of money,” he said, as we had breakfast back in his bungalow. I had fried eggs and a lot of tapioca done very well that they looked like baked potatoes.

I knew that in London Leslie Davidson had advocated using raw materials for buildings, and even for expatriates, he said they could save by eating what is available in the local market and eat like what the locals do, but as usual Bill did not do anything by halves.

“We should be leaving soon to see the country, first to the slave castle at Cape Coast.”

It was in the car that he talked about Al Doku.

“He is going to London on a course that I had arranged for him. But the other reason is it gives him a chance to take his daughter there for treatment. She is losing her eyesight and probably it could be saved by the doctors there.”

“Let him know that I will be in London. I will take him to my house and have lunch with him. He impresses me.”

At the slave castle in Cape Coast, Bill had paid a guide to take us through the full tour. I saw the high white walls and the dark cellars made for the incarceration of human captives. The guide said they were standing in human waste until the time the ship arrived, and they were whipped and pushed through a small exit that all would call the “door of no return”.

We climbed into bright sunlight again to the chapel and the quarters of the commandant. The castle had been fought over by the Swedes, the Norwegians, the Danes and the Dutch before it fell to the English. They traded the slaves in the New World, coming home with cotton and sugar, and out again with cloth and guns to the Gold Coast, and the cycle went on for years.

I was tired after the tour. Bill said to me: “Now I will take you to Elmina castle.”

I did not expect that. It was more or less the same, tiring, as I walked on the hot open yard with rusted cannons lined over the thick stone walls facing the Atlantic below. Coconut trees leaned by the shore where lazy waves lapped away at the sand.

But where our car was parked, we were stopped by many hawkers, who made a brisk business selling handicraft, and what interested me most was the colourful cloth weaved in bright red, yellow and green that I knew was the work of skilled people. The pattern attracted me.

“Fine kente cloth, but tourist prices,” Bill said.

“Can you ask Al Doku if he can bring back a piece and I will pay him in London.”

That was how Al Doku met me again and on a weekend. I invited him for lunch with my family in Surrey and he brought the piece of cloth. It must have cost him a lot of money, and I did not mind paying him a premium for his effort, and it was very beautiful, and probably fit for a minor chief to wear in Ghana.

His daughter was getting medical treatment at a hospital.

I did not hear of Al Doku for many years after I left Unilever, but I still thought of his visit and the lunch like it was yesterday. I had always wondered how he got on after all these years. I remembered him warmly.

By chance, I met him again when he was attending an oil palm conference in Kuala Lumpur. It was just before the conference dinner. I was delighted to see him again and hugged him. I felt a glow of old friendship.

“But I don’t remember you,” he said.

I drew back and explained that he was my guest for lunch in England, and I had bought the kente cloth. I asked him how his daughter was.

But he still could not remember me. Long years had passed but surely he could not have forgotten.

I was told by then he was the managing director of the plantation business. I was upset through the courses of the dinner.

It was at the dessert stage that Al Doku walked up to my table and said with a smile.

“I am so sorry I could not remember you. I think I can remember you now.”

He tried to smile again.

“That’s all right,” I said returning to my dessert.

He tried to be nice to me but the glow of friendship was gone.

The writer has extensive experience in the management of oil palm plantations. Comments: letters@thesundaily.com

TOY manufacturer Mattel have removed thousands of its ‘Wicked’-branded dolls off the shelves after discovering a x-rated printing error on the packaging.

The dolls were made in collaboration with the movie adaptation of the award-winning musical ‘Wicked’, fashioned after the characters.

CNBC reported that the website link printed on the dolls’ packaging lead to a pornographic website instead of the ‘Wicked’ movie adaptation’s official website.

Quoting Mattel’s apology statement, the company stated it was “aware” of a misprint on the doll’s packaging, mainly sold in US, intended to direct consumers to the movie’s landing page.

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“We deeply regret this unfortunate error and are taking immediate action to remedy this. Parents are advised that the misprinted, incorrect website is not appropriate for children,” Mattel was quoted as saying.

The company also advised consumers who have already purchased the dolls with the misprint to throw away the packaging or “obsure”, as quoted, the website link.

Following the misprint revelation, several online retailers across the US have pulled the dolls off their shelves as of Monday (Nov 11).

However, it is unclear if the toy manufacturing company will release the dolls with the correct print details or provide stickers to cover the mistakenly printed link.

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